A conceptual and computational framework for modelling and understanding the non-equilibrium gene regulatory networks of mouse embryonic stem cells.
A conceptual and computational framework for modelling and understanding the non-equilibrium gene regulatory networks of mouse embryonic stem cells.
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DOI：
10.1371/journal.pcbi.1005713
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发表时间：
2017-09
影响因子：
4.3
通讯作者：
Halley JD
中科院分区：
文献类型：
--
作者：
Greaves RB;Dietmann S;Smith A;Stepney S;Halley JD
多能胚胎干细胞分化成体内任何细胞类型的能力使其在再生医学领域具有不可估量的价值。然而，由于核心多能性网络和细胞命运计算过程的复杂性，尚不可能控制干细胞的命运。我们提出了一个基于Halley和Winkler的分支过程理论（BPT）和Greaves等人的干细胞命运计算的理论模型。的基于代理的计算机模拟从理论模型。BPT将转录因子（TF）的复杂生产和作用抽象为一个单一的关键分支过程，该过程可能会消散，维持或变得超临界。在这里，我们采取单一的TF模型，并将其扩展到多个相互作用的TF，并建立一个基于代理的仿真多个TF研究这种耦合系统的动力学。我们已经开发了模拟和理论模型，在一个迭代的方式，以获得更深入的了解干细胞命运计算的目的，以影响实验的努力，这反过来可能会影响细胞分化的结果。所使用的模型是自组织的一个例子，可以更广泛地适用于其他复杂系统的建模。基于此模型的模拟，虽然目前有限的范围内，它所代表的生物学，支持实用程序的哈雷和温克勒分支过程模型在描述干细胞基因调控网络的行为。我们的模拟演示了三个关键特征：（i）分支过程参数的临界值的存在，取决于所讨论的顺反子的细节;（ii）活性顺反子“点燃”否则完全耗散的顺反子的能力，并将其驱动到临界状态;（iii）如何将顺反子耦合在一起可以减少驱动它们到临界状态所需的临界分支参数值。多能干细胞具有无限自我更新和分化为体内任何细胞类型的能力。因此，指导干细胞分化的能力将在再生医学中具有巨大的潜力。有大量与干细胞相关的生物学数据;在这里，我们利用与干细胞分化相关的数据来帮助理解细胞行为和复杂性。这些细胞包含一个动态的、非平衡的基因网络，该网络部分地由网络本身表达的转录因子调节。在这里，我们采用了一个现有的理论框架，转录因子分支过程，它解释了这些遗传网络如何具有关键行为，并且可以在低表达和完全表达之间倾斜。我们使用这一理论作为基础的设计和实现的计算模拟平台，然后我们使用它来运行各种模拟实验，以更好地了解这些不同的转录因子如何可以联合收割机，相互作用，并相互影响。模拟参数来自与多能干细胞分化中的核心因素有关的实验数据。模拟结果确定了分支过程参数的临界值，以及这些参数是如何被各种相互作用的转录因子所调节的。
The capacity of pluripotent embryonic stem cells to differentiate into any cell type in the body makes them invaluable in the field of regenerative medicine. However, because of the complexity of both the core pluripotency network and the process of cell fate computation it is not yet possible to control the fate of stem cells. We present a theoretical model of stem cell fate computation that is based on Halley and Winkler’s Branching Process Theory (BPT) and on Greaves et al.’s agent-based computer simulation derived from that theoretical model. BPT abstracts the complex production and action of a Transcription Factor (TF) into a single critical branching process that may dissipate, maintain, or become supercritical. Here we take the single TF model and extend it to multiple interacting TFs, and build an agent-based simulation of multiple TFs to investigate the dynamics of such coupled systems. We have developed the simulation and the theoretical model together, in an iterative manner, with the aim of obtaining a deeper understanding of stem cell fate computation, in order to influence experimental efforts, which may in turn influence the outcome of cellular differentiation. The model used is an example of self-organization and could be more widely applicable to the modelling of other complex systems. The simulation based on this model, though currently limited in scope in terms of the biology it represents, supports the utility of the Halley and Winkler branching process model in describing the behaviour of stem cell gene regulatory networks. Our simulation demonstrates three key features: (i) the existence of a critical value of the branching process parameter, dependent on the details of the cistrome in question; (ii) the ability of an active cistrome to “ignite” an otherwise fully dissipated cistrome, and drive it to criticality; (iii) how coupling cistromes together can reduce their critical branching parameter values needed to drive them to criticality. Pluripotent stem cells possess the capacity both to renew themselves indefinitely and to differentiate to any cell type in the body. Thus the ability to direct stem cell differentiation would have immense potential in regenerative medicine. There is a massive amount of biological data relevant to stem cells; here we exploit data relating to stem cell differentiation to help understand cell behaviour and complexity. These cells contain a dynamic, non-equilibrium network of genes regulated in part by transcription factors expressed by the network itself. Here we take an existing theoretical framework, Transcription Factor Branching Processes, which explains how these genetic networks can have critical behaviour, and can tip between low and full expression. We use this theory as the basis for the design and implementation of a computational simulation platform, which we then use to run a variety of simulation experiments, to gain a better understanding how these various transcription factors can combine, interact, and influence each other. The simulation parameters are derived from experimental data relating to the core factors in pluripotent stem cell differentiation. The simulation results determine the critical values of branching process parameters, and how these are modulated by the various interacting transcription factors.
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影响因子：
9.8
作者：
Lowell, Sally;Benchoua, Alexandra;Heavey, Barry;Smith, Austin G
通讯作者：
Smith, Austin G
影响因子：
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作者：
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通讯作者：
Tobias, AM
影响因子：
1.3
作者：
Halley, JD;Burd, M
通讯作者：
Burd, M
影响因子：
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作者：
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通讯作者：
Deneubourg, J. L.
影响因子：
7.9
作者：
Xu, Huilei;Schaniel, Christoph;Lemischka, Ihor R.;Ma'ayan, Avi
通讯作者：
Ma'ayan, Avi